How to use Flux(v6.9.0) to filter through fuzzy(Imprecise) queries(regular expression)?

[isMrZhang]

Proposal: Filter fuzzy(Imprecise) queries by tag or field.

Current behavior: Finding that there is no imprecise filtering query method or regular expression filtering method, I tried using custom but he doesn't work as expected.

Flux flux = Flux
            .from("basic")
            .range(Instant.now(), Instant.now())
            .filter(Restrictions.and(
                    Restrictions.measurement().equal("api_log"),
                    Restrictions.tag("org_id").equal("EDUCLOUD"),
                    Restrictions.tag("title").custom("/account/", "=~"))
            .pivot(List.of("_time"), List.of("_field"), "_value")
            .group()
            .sort(List.of("_time"), true)
            .limit(10, (0 - 1) * 10);

anticipate:

from(bucket:"basic")
    |> range(start:2023-07-14T15:59:59.000000000Z, stop:2023-07-14T15:59:59.000000000Z)
    |> filter(fn: (r) => (r["_measurement"] == "api_log" and r["orgId"] == "EDUCLOUD" and r["title"] =~ /account/))
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
    |> group()
    |> sort(columns:["_time"], desc:true)
    |> limit(n:10, offset:0)

actual:

from(bucket:"basic")
    |> range(start:2023-07-14T15:59:59.000000000Z, stop:2023-07-14T15:59:59.000000000Z)
    |> filter(fn: (r) => (r["_measurement"] == "api_log" and r["orgId"] == "EDUCLOUD" and r["title"] =~ "/account/"))
    |> pivot(rowKey:["_time"], columnKey:["_field"], valueColumn:"_value")
    |> group()
    |> sort(columns:["_time"], desc:true)
    |> limit(n:10, offset:0)

error: com.influxdb.exceptions.InternalServerErrorException: HTTP status code: 500; Message: type error 3:88-3:109: string != regexp

Desired behavior: Imprecise filter query method or regular expression filter method, custom filter regular expression is normal

Alternatives considered: Restrictions.custom() In the tank regular expression

Use case: Regular expressions (regular expressions) are very powerful when matching patterns in large data collections, and they can effectively filter the amount of data.

[KYankee6]

same problem here. is there any update?